Making AI Work Legible: Transparency, Reproducibility, and Trust
Lunch Hour Workshop
When
**NEW DATE** Thursday, July 30th
IN-PERSON 12:00 – 1:00pm
ZOOM 2:00 – 3:00pm
Where
**NEW LOCATION** School of Data Science, Classroom 305, 1919 Ivy Road, Charlottesville, VA 22903
Instructor: Alex Gates, School of Data Science
How to document and justify the use of Al in research so that workflows remain interpretable, reproducible, and credible. Covers where Al enters the research pipeline, common failure modes, and practical strategies for disclosure, validation, and communicating methods in papers and proposals.
Who should take this: Faculty across disciplines, especially those incorporating Al into writing, literature review, qualitative analysis, or data workflows, who want their work to remain rigorous and reviewable.